pickgene(pickgene)
pickgene()所属R语言包:pickgene
Plot and Pick Genes based on Differential Expression
根据图和匹克基因差异表达
译者:生物统计家园网 机器人LoveR
描述----------Description----------
The function picks plots the average intensity versus linear contrasts (currently linear, quadratic up to cubic) across experimental conditions. Critical line is determine according to Bonferroni-like multiple comparisons, allowing SD to vary with intensity.
功能选择图跨越的实验条件与线性对比(目前线性,二次立方)的平均强度。临界线是根据邦弗朗尼般的多重比较确定,允许的SD与强度的不同而有所差异。
用法----------Usage----------
pickgene(data, geneID = 1:nrow(data), overalllevel = 0.05,
npickgene = -1, marginal = FALSE, rankbased = TRUE,
allrank = FALSE, meanrank = FALSE, offset = 0,
modelmatrix = model.pickgene(faclevel, facnames,
contrasts.fac, collapse, show, renorm), faclevel =
ncol(data), facnames =
letters[seq(length(faclevel))], contrasts.fac =
"contr.poly", show = NULL, main = "", renorm = 1,
drop.negative = FALSE, plotit = npickgene < 1, mfrow
= c(nr, nc), mfcol = NULL, ylab = paste(shownames,
"Trend"), ...)
参数----------Arguments----------
参数:data
data matrix
数据矩阵
参数:geneID
gene identifier (default 1:nrow(x))
基因标识(默认1:nrow(x))
参数:overalllevel
overall significance level (default 0.05)
整体显着性水平(默认0.05)
参数:npickgene
number of genes to pick (default -1 allows automatic selection)
基因的数量来接(默认的-1允许自动选择)
参数:marginal
additive model if TRUE, include interactions if FALSE
添加剂,如果真实的模型,包括相互作用,如果为FALSE
参数:rankbased
use ranks if TRUE, log tranform if FALSE
如果真使用行列,如果为FALSE登录变换的
参数:allrank
rank all chips together if true, otherwise rank separately
排名所有芯片一起,如果属实,否则单独排名
参数:meanrank
show mean abundance as rank if TRUE
显示平均丰度为排名如果为TRUE
参数:offset
offset for log transform
log变换抵消
参数:modelmatrix
model matrix with first row all 1's and other rows corresponding to design contrasts; automatically created by call to model.pickgene if omitted
第一行的矩阵模型所有1和相应的设计对比其他行;自动创建呼叫model.pickgene如果省略
参数:faclevel
number of factor levels for each factor
每个因子因子水平
参数:facnames
factor names
因素名称
参数:contrasts.fac
type of contrasts
类型对比
参数:show
vector of contrast numbers to show (default is all)
向量的对比数字显示(默认为全部)
参数:main
vector of main titles for plots (default is none)
向量图的主标题(默认为无)
参数:renorm
vector to renormalize contrasts (e.g. use sqrt(2) to turn two-condition contrast into fold change)
向量renormalize反差(例如使用sqrt(2)变成fold change两个条件相反)
参数:drop.negative
drop negative values in log transform
下降log变换负值的
参数:plotit
plot if TRUE
图如果为TRUE
参数:mfrow
par() plot arrangement by rows (default up to 6 per page; set to NULL to not change)
par()行图安排(每页6默认设置为NULL不改变)
参数:mfcol
par() plot arrangement by columns (default is NULL)
par()列(默认为空)的图安排
参数:ylab
vertical axis labels
垂直轴标签
参数:...
parameters for robustscale
robustscale参数
Details
详情----------Details----------
Infer genes that differentially express across conditions using a robust data-driven method. Adjusted gene expression levels A are replaced by qnorm(rank(A)), followed by robustscale estimation of center and spread. Then Bonferroni-style gene by gene tests are performed and displayed graphically.
推断基因的差异表达整个使用一个强大的数据驱动方法的条件。调整后的基因表达水平A取代qnorm(rank(A)),robustscale中心和蔓延的估计。然后邦弗朗尼式的基因测试基因进行图形显示。
值----------Value----------
Data frame containing significant genes with the following information:
数据框包含以下信息的重要基因:
参数:pick
data frame with picked genes
挑选基因的数据框
参数:score
data frame with center and spread for plotting
数据框中心和蔓延的图
Each of these is a list with elements for each contrast. The pick data frame elements have the following information:
这些是每个对比的元素的列表。 pick数据框元素有以下信息:
参数:probe
gene identifier
基因标识
参数:average
average gene intensity
基因平均强度
参数:fold1
positive fold change
正的fold change
参数:fold2
negative fold change
负倍
参数:pvalue
Bonferroni-corrected p-value
邦弗朗尼校正p值
The score data frame elements have the following:
score数据框元素有以下几种:
参数:x
mean expression level (antilog scale)
平均表达水平(反对数规模)
参数:y
contrast (antilog scale)
对比度(反对数刻度)
参数:center
center for contrast
作为对比中心
参数:scale
scale (spread) for contrast
对比规模(传播)
参数:lower
lower test limit
较低的测试极限
参数:upper
upper test limit
上测试极限
作者(S)----------Author(s)----------
Yi Lin and Brian Yandell
参考文献----------References----------
“Robust Data-Driven Inference for Gene Expression Microarray Experiments,” Technical Report, Department of Statistics, UW-Madison.
参见----------See Also----------
pickgene
pickgene
举例----------Examples----------
## Not run: [#无法运行:]
pickgene( data )
## End(Not run)[#结束(不运行)]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
注1:为了方便大家学习,本文档为生物统计家园网机器人LoveR翻译而成,仅供个人R语言学习参考使用,生物统计家园保留版权。
注2:由于是机器人自动翻译,难免有不准确之处,使用时仔细对照中、英文内容进行反复理解,可以帮助R语言的学习。
注3:如遇到不准确之处,请在本贴的后面进行回帖,我们会逐渐进行修订。
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